Location
10 Paternoster Square, London

Hours
Full Time

Salary
Negotiable

About the Role
Are you an experienced Data Science leader with a passion for building and scaling AI/ML products? Join London Stock Exchange Group as a Data Science Manager and lead a team of exceptional Data Scientists and ML Engineers to build next-generation AI solutions for financial markets. Drive innovation using Large Language Models (LLMs), Generative AI, Deep Learning, Transformers, Agentic AI, and advanced Machine Learning to deliver real-world business impact. This role combines technical leadership, people leadership, and strategic execution to deliver production-grade AI-powered products that create measurable business value at scale. You will establish engineering excellence, develop exceptional talent, and partner closely with Product, Engineering, Research, and business teams to shape strategy and accelerate execution. If you are passionate about shaping the future of AI and leading high-impact AI initiatives, we'd love to talk to you.

Key Responsibilities
Lead the design, development, evaluation, and deployment of scalable AI and Machine Learning solutions. Drive innovation in Generative AI, LLMs, Agentic AI, Retrieval-Augmented Generation (RAG), Deep Learning, and Transformer architectures. Define the technical vision ensuring solutions are secure, maintainable, and aligned with business goals. Provide expertise in model development, experimentation, optimization, and production deployment. Establish methodologies for LLM evaluation, benchmarking, AI quality measurement, and performance assessment. Evaluate emerging AI technologies and guide architectural decisions across AI platforms, model-serving infrastructure, data pipelines, and MLOps/LLMOps capabilities. Build, mentor, and lead high-performing teams, fostering a culture of innovation, collaboration, and continuous learning. Partner with cross-functional teams to define AI strategy, roadmap, and priorities, ensuring delivery of high-quality AI solutions with measurable business value. Champion engineering excellence, responsible AI practices, model governance, compliance, and operational risk management.

About London Stock Exchange Group
Join a global leader in financial markets infrastructure and data, committed to innovation, quality, and continuous improvement. LSEG values integrity, partnership, excellence, and change, fostering a diverse and inclusive culture where individuals can bring their true selves to work. With 25,000 colleagues across 65 countries, LSEG offers a collaborative and creative environment, supporting sustainability and community engagement through the LSEG Foundation. Enjoy tailored benefits including healthcare, retirement planning, paid volunteering days, and wellbeing initiatives.

Experience
- Proven track record of building, leading, and developing high-performing teams of Data Scientists, ML Engineers, and AI practitioners.
- Demonstrated success delivering large-scale AI initiatives from ideation to production with measurable business impact.
- Experience leading multiple concurrent programs, balancing priorities, resources, and customer expectations.
- Extensive experience designing, building, and deploying production-grade AI and Machine Learning solutions at scale.
- Deep expertise in LLMs, Generative AI, RAG, Agentic AI, Deep Learning, Neural Networks, and Transformer architectures.
- Hands-on experience with LLM evaluation, benchmark design, model validation, prompt engineering, guardrails, and AI quality assessment.
- Advanced proficiency in Python and modern AI frameworks such as PyTorch, TensorFlow, Scikit-Learn, Hugging Face, LangChain, and Semantic Kernel.
- Experience building and scaling enterprise AI platforms, ML infrastructure, and intelligent applications.
- Strong understanding of model observability, monitoring, evaluation frameworks, experimentation, and operational excellence.
- Expertise in cloud-native AI development using Azure AI Foundry, Azure Machine Learning, Azure OpenAI, Azure AI Search, AWS AI Services, and modern cloud architectures.
- Experience implementing MLOps and LLMOps practices including CI/CD, model lifecycle management, governance, and production operations at scale.
- Ability to communicate complex technical concepts clearly to technical, business, and executive audiences.
- Strong stakeholder leadership skills with a proven track record to drive alignment across Product, Engineering, Research, and Business teams.

About You
Exceptional leadership, communication, and influencing skills with experience engaging senior leadership and executive collaborators. Passionate about fostering a culture of innovation, collaboration, ownership, and continuous learning. Skilled at coaching, mentoring, performance management, and talent development. Able to balance strategic vision with hands-on technical expertise. Committed to responsible AI, model governance, compliance, and operational risk management.

Qualifications
Bachelor's degree or equivalent experience in Computer Science, Data Science, Statistics, Mathematics, Engineering, Physics, Artificial Intelligence, Machine Learning, or a related quantitative field. Master's degree or PhD preferred. Experience in financial services, capital markets, research, analytics, or other data-intensive domains is desirable. Knowledge of reinforcement learning, fine-tuning, synthetic data generation, model compression, advanced optimization techniques, Knowledge Graphs, vector databases, semantic search, retrieval systems, and Graph RAG architectures is a plus. Familiarity with DevOps, CI/CD, Kubernetes, Infrastructure as Code, containerization, and distributed computing platforms is advantageous. Contributions to the AI community through publications, patents, conference presentations, research, or open-source projects are welcomed.